# Questions tagged [superresolution]

Super-resolution refers to a class of techniques to enhance the resolution of a (digital) signal.

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### synchronize adcs with neuronal network

if i have two adcs(analog to digital converters) sampling a signal. Is it possible to synchronize the two adcs with deep learning? as far as i know, with super-resolution on image processing it is the ...
44 views

### Whats the difference between spatial and temporal resolution?

Iam trying to understand how super-resolution works. But i think i have not understood correctly the difference between the optical resolution (spatial resolution?) and the resolution i know from a ...
58 views

### Super resolution with aliased signal

SKIP to Questions below if you want : In super resolution I can create a high resolution signal from a low resolution signal. But it is also possible that the low resolution signal contains aliasing. ...
52 views

### How to find correlation between two signals regarding peaks?

In a super-resolution task, I try to predict the higher frequencies of a signal. X low-resolution (lr) is my input and Y high-resolution (hr) is the target. Where X contains only frequencies till 2 ...
61 views

### Element-wise powering vs. discrete version of binomial theorem on a sum of Gaussians

I had recently posted a question on applying powers on a sum of Gaussians (here) to enhance signal resolution artificially. The discussion has given rise to another query. Consider this problem. We ...
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### Applying a Power on a Sum of Gaussians to Enhance Resolution

There is so-called Power Transform technique in signal processing where the unresolved signal is sharpened by raising each data to a constant positive power. The example shown below is a sum of two ...
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### Recommended Order of Performing Denoising, Deblurring and Super Resolution on an Image

In the normal workflow of image processing, there are multiple operations, increase image contrast, image denoising, image deblur and image super-resolution. What are the sequence/order of performing ...
34 views

### What is the Assumptions behind obtaining Better Frequency Resolution based on Transformation of the Random Variables?

If the sequence is short (N is small), we cannot resolves frequencies being closed together (even by some tricks like zero padding). One way to solve it is to create a pseudo-sequence from the ...
88 views

### Converting very short “motionless” video frames to single, better-resolved, images

I made a mistake with my newly bought compact camera, before a trip to Japan. Instead of taking single pictures, I ended up with a few short "MP4" video files (1 second, 2-3 frames). I could ...
161 views

### Resolution of MUSIC algorithm

MUSIC algorithm has been known to provide super-resolution imaging capabilities, and it is implemented in target recognition radar system, however, I couldn't find a definite expression for its ...
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### What Are the Differences between Super Resolution, Denoising and Deblurring?

In the fields of computer vision and image processing, what are the differences between Super Resolution, Denoising and Deblurring?
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### Signal Resampling by a non integer factor with convolution

to start I am a newbie in signal processing, I just started a month ago so please be as detailed as possible. From what I understood to resample a signal by a non integer factor you can do an ...
132 views

### Why would super resolution using deep learning beat the old school techniques?

I assume a standard/ old school super resolution techniques use Polynomial interpolation and Upsampling approaches. Why would deep neural networks achieve better results?
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### Obtaining Subpixel Resolution for Video Processing in Python

I am working on a video processing application to calculate distance between two points using opencv Specs : Linear Pixels - 1600. FOV - 100 mm Resolution per pixel using above data : 62 micron ...
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### Super- resolution: Warp Matrix

The super resolution model is as such: Y_k = DHFX + N , where Y_k is one of the N measured low resolution image, D is the Decimation Matrix, H is the blur matrix , F is the warp matrix, N is the noise ...
153 views

### Super resolution methods

I am working on the project where my goal is to create SR image from 25 LR images that are precisely shifted by 0.2px (both in horizontal and vertical direction ). I also know that the captured object ...
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### Best (Perceptually / Objectively) Super Resolution Methods Out There?

I'm curious about the advances in the area of image super-resolution (SR) that have given the best results to date, both perceptually (visually pleasing) and objectively (e.g. PSNR, SSIM criterias). I'...
136 views

### Calculate Horizontal Pixel Shift for Super Resolution

I have a sample that is moving at a constant rate which is known. Since I know the distance traveled I can equate that with the number of pixels for the pixels shift. The only way I can think to do ...
11k views

### Subpixel - what is it?

I'm studying SuperResolution techniques, and I read often "subpixel"/"subpixel registration"/"subpixel accuracy". I don't find what exactly it means; Wikipedia says that is one of the three RGB ...
531 views

### What is the state-of-the-art of using signal-processing for “cleaning-up” videos?

TWO PART QUESTION - We've all seen the movies/TV shows where the police/feds/spies use computer software to take a grainy photo and do a "clean-up" to see a better picture and more details. I assume ...
603 views

### optimization of Image Reconstruction Algorithm using Genetic Algorithm in Matlab

I'm trying to optimize an image reconstruction algorithm using genetic algorithm.I took initial population size as 10.I have an input image an 10 reconstructed image.fitness function is the difference ...
3k views

### Image super resolution algorithm in Matlab

I'm trying to implement a simple Image super resolution algorithm (DWT-Based Resolution Enhancement ) in the following paper http://www.ripublication.com/aeee/52_pp%20%20%20405-412.pdf I tried to ...
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### What's the Underlying Algorithm for Detail Preserving Upsampling in Photoshop CC?

The detail-preserving upsampling algorithm in Photoshop CC is truly amazing. It can upscale any image while preserving details in almost real-time. And I truly wonder how it is implemented. I've ...
109 views

### will always periodogram produce correct frequencies?

let say we have some data,some signal written in this form $x(t)=s(t)+\epsilon(t)$ where $s(t)$ is pure signal and $\epsilon(t)$ is white noise with mean zero and some variance ,question is ...
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### use wavelet for improving spectral resolution

let us consider following code ...
863 views

### ARMA models for non stationary signals

let us suppose that we have non stationary signal,whose value is given by ...
458 views

### Motion and Distortion Estimation using multiple still images?

TL/DR: I'd like to take the median of lots of images to make a single "better" image. The problem is, the camera is slowly moving, and there is significant lens distortion. On the plus side the ...
331 views

### Artifacts in image after super resolution using delaunay triangulation in MATLAB

i have to do super resolution of two low resolution images to obtain a high resolution image. 1st image is taken as base image and the second image is registered with respect to it . i used SURF ...
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### Why Is Super Resolution (SR) Possible?

I've been reading about Super Resolution Image reconstruction (Reconstruction of high resolution image from multiple low resolution aliased images contain sub pixel shifts), and i want to know why SR ...
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### Explanation of LidarBoost Algorithm?

I am trying to understand the LidarBoost algorithm as explained in this paper (PDF warning). I don't understand how they take the original depth-images $Y_k$ and transform them into the up-sampled ...
155 views

### Possibility of temporal super resolution

I've been reading some papers in the context of super resolution in imaging and video (for example works by Michal Irani [1], [2] and so forth), and was wondering if a similar idea can be applied with ...